Browse > Article
http://dx.doi.org/10.5351/KJAS.2004.17.3.475

A Comparison Study of Several Robust Regression Estimators under Various Contaminations  

김지연 (인하대 통계학과)
황진수 (인하대 통계학과)
김진경 (인하대 통계학과)
Publication Information
The Korean Journal of Applied Statistics / v.17, no.3, 2004 , pp. 475-488 More about this Journal
Abstract
Several robust regression estimators are compared under contamination. Symmetric and asymmetric contamination schemes are used to measure the variance and MSE of regression estimators. Under asymmetric contamination depth-based regression estimator, especially projection based regression estimator(rcent) outperforms the rest and under symmetric contamination HBR performs relatively well.
Keywords
Breakdown point; Influence function;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Huber, P.J.(1973). Robust, regression: asymptotics, conjectures, and monte carlo. Annals of statistics, 1, 799-821   DOI   ScienceOn
2 Hubert, M., Rousseeuw. P.J., Van Aelst, S. (2001). similarities between location depth and regression depth, Trends in Mathematics, 159-172
3 Hwang, J.S., Jorn, H.S., and Kim, J.K. (2004). On the performance of bivariate robusst location extimators under cotamination, Computaional Statistics Data Analysis, 44, 587-601   DOI   ScienceOn
4 Jaeckel, L.A. (1972). Estimation regression coefficients by minimizing the dispersion of residuals. Annoals of Mathematical Statistics, 43, 1449-1458   DOI   ScienceOn
5 Liy, R.Y., Parelius, J.M., and Singh, K. (1999). Multivariate analysis by data depth: descriptive statistics, graphics and inference, Annals of Statistics, 18, 405-414   ScienceOn
6 Mallows, C.L. (1975). On some topics in robustness. Technical Memorandum, Bell Telephone Laboratories, Myrray hill, New Jersey
7 Rousseeuw, P.J. (1984). Least median of squares regression, Journal of the American Statistical Association, 79, 871-880   DOI   ScienceOn
8 Rousseeuw,P.J., and Hubert, M. (1999). Regression depth, Journal of the American Statistical Association, 94, 388-402   DOI   ScienceOn
9 Rousseeuw,P.J., and Yohau, V.J. (1984). Robust regression by means of s-estimators, Robust and Nonlinear Time Series Analysis, Lecture Notes in Statistics, 26, 256-272, Springer, New York   DOI
10 Single, A.F. (1982). Robust regression using repeated medians, Biometrika, 69, 242-4   DOI   ScienceOn
11 zuo, Y., and Serfling, R. (2000). General notions of statistical depth funstion, Annals of Statistics, 28(2), 461-482   DOI   ScienceOn
12 Hampel, F.R. (1974). The influence curve and its roles in robust estimation. Journal of the American Statistical Association, 69, 383-393   DOI   ScienceOn
13 Chang, W.H., Mckean, J.W., Naranjo, J.D., and Sheather,S.J. (1999). High breakdown rank regression, Journal of the American Statistical Association, 94, 445, Theory and Methods
14 Donoho, D.L., and Huber, P.J. (1983). The notion of breakdown point, in: P.J. Bickel, K.A.DokSum and Hodges, Jr., eds, A Fesrschrift fee Erich L. Lehmann, Wadsworth, Belmont, CA, 157-184